SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 181–190 of 4891 papers

TitleStatusHype
MonoSplat: Generalizable 3D Gaussian Splatting from Monocular Depth Foundation ModelsCode2
MOROCCO: Model Resource Comparison FrameworkCode2
Fast FullSubNet: Accelerate Full-band and Sub-band Fusion Model for Single-channel Speech EnhancementCode2
BiFormer: Vision Transformer with Bi-Level Routing AttentionCode2
Fast-SNARF: A Fast Deformer for Articulated Neural FieldsCode2
Advances in 4D Generation: A SurveyCode2
FastBlend: a Powerful Model-Free Toolkit Making Video Stylization EasierCode2
Data-Driven Parametrization of Molecular Mechanics Force Fields for Expansive Chemical Space CoverageCode2
On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?Code2
BEBLID: Boosted efficient binary local image descriptorCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified